Examples

Here is a list of example notebooks to illustrate how to access data, create plots, and do machine learning using CliMetLab.

• Reading data from a file
  • Plot GRIB data
  • Plot NetCDF data
• Downloading from an URL
• Retrieve ERA5 data from the CDS
• Retrieve data ECMWF MARS archive
• Access ECMWF Open Data feed
• ERA5-based datasets
  • Surface temperature in France
  • Precipitations from Ireland
• Machine learning example
  • Load the high-low data set and plot all the fields and their label
  • Get the train and test sets
  • Build the model
  • Train the model
  • Plot the predictions
• BUFR data
• ECMWF Observation bespoke format (ODB)
• Meteonet
  • Radar images
  • Ground station observations
  • Weather models
  • Masks
• WeatherBench
• NOAA’s hurricane database
  • Huricanes making landfall at category 5
  • Get the track for Katrina
  • Plot the track
  • Retrieve matching fields from ERA5
  • Pacific bassin
  • Plot each track independently
• External plugins
  • External data source
• More plotting examples
  • Projections
  • Low-level graphical attributes
• Interactive maps
• Creating a shared dataset of GRIBs
  • Download data to the climetlab cache
  • Export the data to a shared directory
  • Create indexes to speed up data access when using it. (Optional)
  • Using the data
• Save data to GRIB
  • A template for the GRIB metadata
  • An numpy array with the data:
  • Write to GRIB
  • Write to GRIB
• Dataset availability